Digital images databases open the way for content-based searching. Content Based Image Retrieval occupies a well ranked position among the research areas as it provides the practical solution for narrowing the semantic gap between the image retrieval process and the human perception. The main objective of this paper is to propose a framework for region content based image retrieval based on a distributed clustered image dataset. The proposed framework introduces a new perspective to measure the similarity between the image query and the clustered dataset images. Moreover, a development by adopting three relevance feedback techniques is used to refine the results of the retrieval system which are the well known Query Point Movement and Query Expansion, besides to the proposed third technique which is Query Modified ReWeighting technique.